Search research articles

Related Concept Videos

Neural Circuits

Neural Circuits

Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Predicting synchronization and oscillation death with parallel reservoir computing.

Physical review. E·2025

Same author

Adaptive control of dynamical systems using reservoir computing.

Chaos (Woodbury, N.Y.)·2025

Same author

Explosive transition in adaptive Stuart-Landau oscillators with higher-order interactions.

Physical review. E·2025

Same author

Tipping in Stuart-Landau oscillators induced by higher-order repulsive interactions.

Physical review. E·2024

Same author

Chimeric states induced by higher-order interactions in coupled prey-predator systems.

Chaos (Woodbury, N.Y.)·2024

Same author

Machine learning approach to detect dynamical states from recurrence measures.

Chaos (Woodbury, N.Y.)·2024

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Search research articles

Related Experiment Video

Updated: Oct 9, 2025

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology

Published on: March 8, 2024

Emergent Dynamics and Spatio Temporal Patterns on Multiplex Neuronal Networks.

Umesh Kumar Verma¹, G Ambika¹

¹Department of Physics, Indian Institute of Science Education and Research Tirupati, Tirupati, India.

Frontiers in Computational Neuroscience

|December 20, 2021

Summary

This study explores how neurons in a multiplex network create spatio-temporal patterns. Different coupling types, like excitatory and inhibitory, lead to synchronized oscillations and pattern selection between layers.

Keywords:

mixed-mode oscillations multi-cluster synchronization multiplex network neuronal network synchronization

More Related Videos

Assessment of the Effects of Endocrine Disrupting Compounds on the Development of Vertebrate Neural Network Function Using Multi-electrode Arrays

Assessment of the Effects of Endocrine Disrupting Compounds on the Development of Vertebrate Neural Network Function Using Multi-electrode Arrays

Published on: April 26, 2018

Multi-electrode Array Recordings of Neuronal Avalanches in Organotypic Cultures

Multi-electrode Array Recordings of Neuronal Avalanches in Organotypic Cultures

Published on: August 1, 2011

Related Experiment Videos

Last Updated: Oct 9, 2025

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology

Published on: March 8, 2024

Assessment of the Effects of Endocrine Disrupting Compounds on the Development of Vertebrate Neural Network Function Using Multi-electrode Arrays

Assessment of the Effects of Endocrine Disrupting Compounds on the Development of Vertebrate Neural Network Function Using Multi-electrode Arrays

Published on: April 26, 2018

Multi-electrode Array Recordings of Neuronal Avalanches in Organotypic Cultures

Multi-electrode Array Recordings of Neuronal Avalanches in Organotypic Cultures

Published on: August 1, 2011

Area of Science:

Computational Neuroscience
Complex Systems
Network Science

Background:

Neurons exhibit complex spatio-temporal dynamics.
Multiplex networks offer a framework to study interconnected systems.
Understanding emergent behavior in coupled neuronal systems is crucial.

Purpose of the Study:

To investigate spatio-temporal pattern emergence in a two-layer multiplex neuronal network.
To analyze the effects of different intralayer and interlayer coupling types (excitatory, inhibitory, electrical).
To explore control mechanisms for pattern selection via coupling strengths.

Main Methods:

Utilized the Hindmarsh-Rose model for single neuron dynamics.
Simulated neuronal activity in a two-layer multiplex network.
Analyzed emergent spatio-temporal patterns under various coupling conditions.

Main Results:

Excitatory coupling led to in-phase synchronized oscillations and amplitude death.
Inhibitory coupling resulted in anti-phase mixed-mode oscillations (MMO) with phase regularities.
Multiplexing revealed pattern transfer and selection between layers, with oscillation revival and phase transitions.
Electrical and synaptic coupling combinations produced synchronized in-phase or anti-phase activity.

Conclusions:

Coupling type and strength significantly influence spatio-temporal patterns in multiplex neuronal networks.
Pattern selection and transfer between layers are controllable phenomena.
The study provides insights into the collective behavior of complex neuronal systems.